Research Article
Research on Radiation Damage Characteristics of Optical Fiber Materials Based on Data Mining and Machine Learning
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@INPROCEEDINGS{10.1007/978-3-030-36402-1_44, author={Ang Li and Tian-hui Wang}, title={Research on Radiation Damage Characteristics of Optical Fiber Materials Based on Data Mining and Machine Learning}, proceedings={Advanced Hybrid Information Processing. Third EAI International Conference, ADHIP 2019, Nanjing, China, September 21--22, 2019, Proceedings, Part I}, proceedings_a={ADHIP}, year={2019}, month={11}, keywords={Data mining Machine learning Fiber material Radiation damage characteristics}, doi={10.1007/978-3-030-36402-1_44} }- Ang Li
Tian-hui Wang
Year: 2019
Research on Radiation Damage Characteristics of Optical Fiber Materials Based on Data Mining and Machine Learning
ADHIP
Springer
DOI: 10.1007/978-3-030-36402-1_44
Abstract
In order to better analyze the damage characteristics of fiber materials under radiation environment, combined with data mining algorithm to calculate the degree of damage of material structure damage. Combine with machine learning method to analyze the calculation results, obtain the damage range of fiber material structure, standardize material damage characteristics and Grade, accurately determine the damage of material structure, and finally improve the radiation damage characteristics of fiber materials. Experiments show that the research on radiation damage characteristics of fiber materials based on data mining and machine learning is accurate and reasonable.
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